Geolocation

ABSTRACT

In selected embodiments, a process of geolocation of a transmitter uses a receiver with an antenna array that is non-line-of-sight (NLoS) to the transmitter. A first plurality of scatterers within line-of-sight (LoS) of the array is located using multilateration based on time difference of arrival (TDoA) from the first scatterers, and applying a spatial consistency requirement. Time of emission/reflection from the first scatterers is also determined. The coordinates and timing of the first scatterers are used to locate either the transmitter or another set of scatterers, by applying multilateration to the TDoA at the first scatterers, and applying the spatial consistency requirement. The process is iteratively repeated until the transmitter is identified. The multilateration may be linearized without sacrificing precision. In each iteration, a non-singularity requirement is applied to ensure that the selected scatterers produce unambiguous results.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation and claims priority from U.S.patent application Ser. No. 13/738,548, entitled GEOLOCATION, filed onJan. 10, 2013, now allowed; which claims priority from U.S. ProvisionalPatent Application Ser. No. 61/586,675, entitled GEOLOCATION, filed on13 Jan. 2012; the U.S. patent application Ser. No. 13/738,548 also claimpriority from U.S. Provisional Patent Application Ser. No. 61/597,492,entitled GEOLOCATION, filed on 10 Feb. 2012. Each of theabove-referenced patent documents is hereby incorporated by reference inits entirety as if fully set forth herein, including text, figures,claims, tables, computer program listing appendices, matter incorporatedby reference in the patent document, and all other matter in thedocument.

FIELD OF THE INVENTION

This document is related to the field of tracking of transmissionsources and other objects, and geolocation, including self-location.Selected disclosed embodiments relate to apparatus, methods, andarticles of manufacture for passive and active geolocation oftransmission sources in various environments, including, withoutlimitation, environments with severe multipath and non-line-of-sight(NLoS) geometries without detectable or easily identifiableline-of-sight (LoS) signal component. Selected disclosed embodimentsrelate to apparatus, methods, and articles of manufacture forpositioning, such as positioning performed by satellite-based globalpositioning systems.

BACKGROUND

Geolocation is a term that describes a broad range of technologies forderiving the spatial location (e.g., X. Y, Z Cartesian coordinates) ofan object by processing transmitted signals that are received, emitted,or reflected by that object. While in selected embodiments described inthis document and illustrated in the attached drawings the transmittedsignals are radio frequency (RF) signals, geolocation and selectedprinciples described here may be extended to other transmitted signals,including sound/ultrasound signals.

Known geolocation examples include the Global Positioning Satellite(GPS) systems and cell phone networks, but other RF geolocation systemsmay be used in areas as diverse as inventory management, asset tracking,law enforcement, and the military. There are several different modes ofoperation of these systems. For example, the GPS systems attempt toenable an object to geolocate its own position by reading RF signalsemitted by multiple satellites. The RF signals contain preciseinformation about the location of the satellites and the time ofemission of the signals. The object can acquire the signals from themultiple satellites, read the data contained in the signals, usestandard multilateration techniques to calculate the coordinates of theobject's position relative to the satellites, and project thecoordinates onto pre-defined references, such as maps. (Multilaterationtechniques are based on the measurement of the difference in distancefrom the located object to two or more stations at known locations thatbroadcast at known times.) For example, the coordinates may be used by avehicle's software to indicate the position of the vehicle on a map, andto map a path to another set of coordinates.

Cellular telephone systems may also perform geolocation. In this case,however, a cell phone can geolocate its position by using data acquiredfrom cell towers in a manner similar to that used by the GPS systems. Inthe cell systems, the technique can also be used in reverse, where thecell network geolocates the cell phone using signals received bymultiple cell towers from the cell phone. This technique is often usedby law enforcement to track individuals.

Similar techniques can be used in inventory management where radiofrequency identifier (RFID) tags can emit signals which can be, e.g.,triangulated by antenna arrays placed around warehouses or in locationslike docks and shipping holds.

In the above-described cases, the geolocation may be achieved by acombination of geometrical calculations, such as triangulation,trilateration, or multilateration and acquiring critical transmissiondata by reading key information embedded in the signals by thetransmission source or some other part of the system. For example, theGPS system embeds in the signal highly precise information about the X,Y, Z coordinates of the satellites and the signal emission times(ephemeris data). If this data can be read on a precise receiver thathas the same time reference as the satellite time reference, thedistances from the receiver to the satellites can be calculated. Thereceiver's location can then be determined through trilateration.

It is more problematic to geolocate through derivation of the criticalspatial parameters of a source without being able to read theinformation content of the source's signal. The process of geolocationbased on the ability to detect the signal at the physical layer is moregeneral and does not necessarily require receivers with specialproperties or a functioning sophisticated infrastructure like the GPSsystems or the cellular telephone systems.

Techniques that perform geolocation based on the physical layerdetection of the signals generally attempt to look at one or moreproperties of the signal, and measure how these properties change asfunction(s) of some spatial variable(s). A large dish antenna, forexample, can be rotated until the received signal is maximized in aparticular direction. This provides direction of arrival (DoA)information. If the result from one antenna is compared with similarresults taken from additional, spatially diverse antennas/locations,triangulation may reveal the apparent source of the signal. Similarly,using the time difference of arrival (TDoA) of signals between or amongmultiple antennas at different known locations, the antenna array can beemployed to geolocate a source by using the time of arrival to estimatethe sides of the triangles rather than the angles, and performtrilateration as opposed to triangulation. Analogous techniques can beused by employing other signal properties, such as detected signalstrength (DSS).

In general, it is necessary to observe the signals from more than onelocation and to compare the results obtained at the different locations.In practice this may be done by placing different antennas at thevarious locations. It may also be done by moving a single antenna to thedifferent locations and comparing sequential measurements. Either thereceiver or the transmitter, or both end points can be moving orstationary, and the mobility may take place independent of thegeolocation process or be part of the geolocation process. In otherwords, the mobility may be used as part of the geolocation process tosearch for the source, or it may result from moving objects attemptingto geolocate themselves in order to determine their location and/ortrajectory. The former mobility may enhance the accuracy of geolocation,the latter may degrade geolocation accuracy by placing strict timelimits on how rapidly the process must be performed. This may eliminatethe ability to use more computationally complex methodologies.

Spatial correlation and spatial diversity are generally the principlesunderlying such techniques. Spatial correlation refers to the conceptthat if the properties of a source which is emitting a signal are known,as are the details of the environment through which the signal ispropagating, the field of the signal is fully determined (defined) atall points in space.

Spatial diversity, in the context of geolocation, usually refers to theability to measure properties of the field at different points in spaceand from these to determine the degree of spatial correlation of thefield. Spatial correlation refers to the ability to predict certainproperties of a signal emitted into a known spatial environment atvarious locations in the environment. To illustrate spatial diversity(as the concept applies to geolocation), comparing measurements ofsignal properties taken at multiple points in space in a highlyspatially correlated field can be used to calculate the location of thesource of the signal. In general, if a source emits a signal, and thesignal at a sufficient number of points in space is measured (adequatespatial diversity), then if the signal is spatially well-correlated, thelocation of the source may be inferred from the inherent structure ofthe field.

In reality, all fields are spatially correlated since propagation of EMwaves is fully deterministic. Since an observer in practice may not knowthe specific details of the environment through which a signalpropagates, however, then spatial correlation becomes a measure of theobserver's knowledge of the environment and computational ability topredict the field. Hence, if the environment is unknown, the spatialcorrelation degrades and becomes significantly less than perfect and theobserver loses the ability to deduce the location of the source bymaking spatially diverse measurements of the field.

If either of these properties (spatial correlation and spatialdiversity) is degraded, the accuracy of the geolocation may suffer andin some cases geolocation may become impossible with conventionaltechniques. Spatial correlation is primarily degraded when there areunknown elements in the propagation environment that corrupt the signal,such as multipath scattering and structures that attenuate the signal orcause dispersion. A particularly serious degradation may occur whenthere is no LoS signal to the observer locations. In that case, thesignal may only reach the observer by following a multipath scatteringroute and hence the processes that use triangulation or multilaterationgenerally fail to provide an acceptable position estimate. Spatialdiversity is usually degraded by using too few antenna locations or byhaving the diverse locations too close together to resolve the signaldifferences. This can result in the failure of the geolocation process.

Noise, interference, and poor measurement techniques may also degradethe received signal and reduce the quality of geolocation. When theseproblems create a reduction of the accuracy of the geolocation, but thesource location remains at some statistical center, we refer to adegradation of “accuracy.” If this degradation of accuracy is caused bymeasurement noise whose statistical properties are known, then it may bepossible to use statistical estimation theory to recover the meanlocation of the signal and improve the accuracy. This may be equivalent,for example, to providing an observer with many measurement resultsspread over a large area, and informing the observer that the resultsfollow a Gaussian (or other known) distribution. The observer can thenestimate the true location to be at the center of the Gaussian peak,resulting in a highly accurate geolocation, even though the results maybe widely spread out. In reality, the statistics may not be knownsufficiently well, and so the accuracy error can be reduced only to theCramer-Rao limit known from the statistical estimation theory. Themagnitude of accuracy errors based on noise typically scales with theactual distance between the source and the observer.

When there is no detectable LoS signal, the statistical estimationtechnique often appears to reduce the effect of the accuracy errors suchas measurement noise, but the final solution may be at the wronglocation, often very far from the correct location. In practice, thesolution often geolocates the strongest LoS scatterer in the field,instead of the original transmission source. This is a serious form oferror, called a bias error, and it may occur when one attempts toperform triangulation or multilateration without having at least a weak(but detectable) LoS signal to provide spatial correlation.Consequently, conventional state-of-the-art systems apply manysophisticated techniques to ensure that effects like multipathscattering do not degrade the ability to recover even weak LoS signalcomponents, or that they use the NLoS components to infer the LoS.

Hence, although some examples in the scientific literature refer to NLoSgeolocation, they generally do not literally mean geolocating in perfectNLoS conditions, i.e., without a detectable LoS signal. Instead, theytypically mean recovering weak LoS signals that are swamped withmultipath (NLoS signals) or using a-priori knowledge of the geometricalobstacles that are blocking the signal to infer the actual LoS path, orestimating the maximum error of the location by placing bounds on howfar the hidden LoS component can deviate from the visible NLoS signal.These techniques may not work well for deeply hidden sources in what isreferred to as multi-hop or “true” NLoS conditions.

The conventional technique used to obtain geolocation information insevere multi-hop NLoS cases is to use a mobile observer who can followthe signal round the corners. This is similar to how a person can locatemisplaced objects, such as car keys or a wallet, by activating a smallacoustic beeper attached to the objects and following the sound untilthey are found. Such techniques, however, are not generally applicable,have serious security and safety limitations, and are not physicallypossible in many circumstances.

Finally, there are variations in how the signals required to geolocatean object are created. In some cases the object itself may be emittingthe RF signal. For example, the military authorities are interested inthe ability to geolocate insurgents activating roadside bombs with cellphones. Other cases, such as GPS system applications, include multiplesatellites emitting signals, while the object to be geolocated ispassively observing the signals. In other cases, an observer mayactively “ping” the environment, attempting to observe reflections froman object of interest and geolocate the object. Still other techniquesmay use an independent beacon to illuminate a target and attemptgeolocation by observing reflections from the target. Other approachesare possible.

In general, the various applications of geolocation include thefollowing:

Using a passive spatially diverse array to geolocate an active source;

Using an active spatially diverse array to geolocate a passive source;

Performing self-geolocation by observing the spatially diverse emissionsof an active array;

Performing self-geolocation by using a passive array to detect signalsemitted by an active source (active beacon); and

Performing self-geolocation using an active array to reflect signalsfrom a passive source reflector (a passive beacon).

Needs in the art exist for better geolocation techniques, includingtechniques capable of true NLoS geolocation.

SUMMARY

Selected embodiments described in this document enable a transmissionsource to be geolocated in a true NLoS environment where the signalreaching the observer from the transmission source does so as a resultof multipath reflections from scatterers, where information about thelocation of the various scatterers responsible for reflecting the signalis not known a priori, and knowledge of how the source is spatiallyrelated to the scatterers is also not available a priori. In particularembodiments, only the physical layer detection of the signal is used,without requiring the ability to read information from the signal. Someembodiments work in LoS situations successfully managed by existingtechnology, and also extend to NLoS cases. The described techniques mayprovide solutions for NLoS geolocation by stationary observers (e.g.,static listening posts used by the intelligence services or military orlaw enforcement stations), without a requirement for deployedinfrastructures such as distributed sensor nets. The techniques alsowork in LoS and improve geolocation generally, including in both mobileand static cases, and do not necessarily require the observer to changeto different methodologies or techniques when faced with difficult NLoSin severe multipath environments.

In selected embodiments, the described techniques may improveperformance as the amount of multipath increases and consequentlyconstitute a paradigm shift compared to previously known geolocationtechniques, which generally degrade with multipath and consequently maynot be useful in severe multipath environments such as ships or metallichangers and other metallic storage areas.

Some embodiments use a simple linearized (linear) algorithm to calculatethe geolocation results, consequently speeding up possible computationalsolutions, since they do not require non-linear estimation techniquesand iterative processes to resolve the solution. The linear algorithmmay incorporate a simple metric that indicates when the antenna geometrydoes not have the required spatial diversity to perform the geolocation,and may also provide the information required for the user to correctthis deficiency.

In embodiments, the linear algorithm is employed to identify the LoSscatterers, and estimate not only their locations, but also the time ofemission from these LoS scatterers. The results from the LoS scatterersare then used to estimate location of the source transmitter, if thesource transmitter is in the LoS of the scatterers previouslyidentified. If the identified scatterers are not within the LoS of thesource transmitter, the step can be successively repeated to obtainlocation and timing estimates for a second set of scatterers, eventuallyobtaining the location/timing estimates for scatterers within the LoS ofthe source transmitter. From the latter information, the location of thesource transmitter is estimated.

In cases where the receiving antenna array is not within the LoS of thetransmitter, but at least one scatterer is within LoS of both theantenna array and the source transmitter, the location(s) of the atleast one scatterer may be estimated together with the time(s) ofemission from the at least one scatterer. The location of the sourcetransmitter may then be estimated based on the location and timinginformation relating to the at least one scatterer. In this way, themultipath information is used—instead of being suppressed. In a sense,the scatterers are used as virtual receiver antenna elements.

Selected described embodiments employ techniques for geolocating atransmission source to improve positioning system operation inenvironments with impaired or no direct line-of-sight between apositioning system receiver and one or more satellites (or othertransmitters used for self-geolocation).

These and other features and aspects of selected embodiments notinconsistent with the present invention will be better understood withreference to the following description, drawings, and appended claims.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 illustrates an example of multipath signatures observed on threeantennas;

FIGS. 2 and 3 illustrate an example where a source illuminatesscatterers that reflect the energy to an antenna array;

FIGS. 4 and 5 illustrate an example with an overlap of multipath echoes;

FIG. 6 illustrates a spatial diversity requirement;

FIG. 7 illustrates an example of a geolocation technique in a cityscapeenvironment;

FIG. 8 illustrates times of arrival of various multipath impulseresponses for the example of FIG. 7;

FIGS. 9 and 10 illustrate application of a Spatial ConsistencyAlgorithm;

FIGS. 11 and 12 illustrate an example of GPS enhancement through use ofa relay station;

FIG. 13 illustrates selected components of a system that can be used forgeolocation and/or GPS enhancement; and

FIG. 14 illustrates selective steps/blocks of methods for geolocating.

DETAILED DESCRIPTION

In this document, the words “embodiment,” “variant,” “example,” andsimilar words and expressions refer to a particular apparatus, process,or article of manufacture, and not necessarily to the same apparatus,process, or article of manufacture. (The word “example” may also referto a real or simulated setting.) Thus, “one embodiment” (or a similarexpression) used in one place or context may refer to a particularapparatus, process, or article of manufacture; the same or a similarexpression in a different place or context may refer to a differentapparatus, process, or article of manufacture. The expression“alternative embodiment” and similar words and expressions are used toindicate one of a number of different possible embodiments, variants, orexamples. The number of possible embodiments, variants, or examples isnot necessarily limited to two or any other quantity. Characterizationof an item as “exemplary” means that the item is used as an example.Such characterization does not necessarily mean that the embodiment,variant, or example is preferred; the embodiment, variant, or examplemay but need not be a currently preferred embodiment, variant, orexample. All embodiments, variants, and examples are described forillustration purposes and are not necessarily strictly limiting.

The words “couple,” “connect,” and similar expressions with theirinflectional morphemes do not necessarily import an immediate or directconnection, but include within their meaning both direct/immediateconnections and connections through mediate elements.

The expression “processing logic” should be understood as selected stepsand decision blocks and/or hardware for implementing the selected stepsand decision blocks. “Decision block” means a step in which a decisionis made based on some condition, and process flow may be altered basedon whether the condition is met or not met.

“Multilateration” refers to a technique for navigating or geolocating anobject based on the measurement of the difference in distance ortime-of-flight from the object to two or more stations at knownlocations that broadcast signals at known times. Measuring thedifference in distance results in an infinite number of locations thatsatisfy the measurement condition. When these possible locations areplotted, they form a hyperbolic curve. To locate the exact locationalong that curve, a second measurement is taken to a different pair ofstations, to generate a second curve, which intersects with the first.When the two are compared, a small number of possible locations result.In comparison, trilateration uses distances or absolute measurements oftime-of-flight from three or more sites; and triangulation uses themeasurement of absolute angles.

Other and further explicit and implicit definitions and clarificationsof definitions may be found throughout this document.

Reference will be made in detail to one or more embodiments (apparatus,methods, and/or articles of manufacture) that are illustrated in theaccompanying drawings. Same reference numerals may be used in thedrawings and this description to refer to the same apparatus elementsand method steps. The drawings may be in a simplified form, not toscale, and may omit apparatus elements and method steps that can beadded to the described systems and methods, while possibly includingoptional elements and/or steps.

For the purposes of this description, a scenario with a single staticsource and an observer is assumed; the described techniques can beextended to geolocation of multiple sources. It is also assumed that theobserver has the ability to deploy multiple antennas at differentlocations, or move a single antenna to different locations, and that theobserver is capable of measuring the location (e.g., the X, Y, Zcoordinates) of each of the antennas. The antennas are referred to asthe “observer array.” Another assumption is that the antennas/receiversare capable of measuring the time of arrival of the incoming signals,and the apparatus is capable of calculating the TDoA of the signalsacross the multiple antennas. Alternatively, other signal properties atthe antennas may be measured, for example, direction of arrival,polarization, or signal strength. The present description focuses ontime of arrival of the signals, but this technique may be applied tosystems that measure different signal properties as long as theseproperties are deterministically related to the spatial locations of thetransmission source, the observer array, and the scatterers. A furtherassumption is that the system can operate at any frequency andbandwidth, although there may be practical limitations if the bandwidthis so low that the time of arrival of the incoming signals cannot beresolved with the required accuracy. In some instances, it can beassumed that the observer has none of the technical limits on equipmentthat would be typical for the channel users. For example, in a lowbandwidth system, it can typically be assumed that the intended receiveruses a matching low bandwidth receiver to minimize noise, but it wouldalso be assumed that the observer is not limited to such a low receiverbandwidth since the observer may need a higher bandwidth to accuratelymeasure the time of arrival (ToA) of the multipath signatures. It canalso be assumed that various deconvolution techniques for enhancedaccuracy of ToA measurements of signals may be utilized to improveaccuracy in low bandwidth cases. In particular these may be veryeffective if the pulse shape and other properties of the source pulseare known with high accuracy.

In an example, a signal travelling between a transmission source and theobserver in an NLoS channel is divided into a series of LoS steps. To dothis, the information contained in the multipath signature reaching theobserver array is retained and utilized. In an NLoS channel, if a signalreaches the observer array, it must have reflected from scatterers inthe path and some of these scatterers must have LoS to the observer. Inembodiments, the multipath signature on each element of the observerarray is first deconvolved into a Channel Impulse Response (CIR) and theToAs of the various multipath echoes are acquired. Other techniques thatenable an accurate measurement of the arrival time of the multipathechoes may also be used. It is conventional (but not necessary) toreference these arrival times to t=0, the arrival time of the earliestarriving signal on the array. Since it is assumed that each LoSscatterer will multicast its signal to each of the elements in theobserver array, it can be determined which of the multipath echoes oneach array element is associated with each of the scatterers. A SpatialConsistency Algorithm, which is more fully described later, may be usedfor this purpose. This algorithm identifies patterns in the arrivaltimes of the multipath echoes across the antennas that can only resultfrom the signatures being reflected from identical LoS scatterers andconsequently allows assignment of groups of multipath echoes to discretescatterers.

An example of this is shown in the diagram of FIG. 1, which showsmultipath signatures observed on 3 antennas, O1, O2, and O3. Each dot onthe diagram represents a multipath echo on a particular antenna and thearrival time can be read from the horizontal axis. The amplitudes of thesignals are represented by the location of the dots on the verticalaxis. (Amplitude information may not be required for the techniquedescribed below.) The labels s11-s16 represent six scatterers that haveLoS visibility to the observer array and any dot lying inside thevertical dotted lines associated with each scatterer represents an echothat was reflected from that particular scatterer.

A first geolocation stage of the LoS scatterers can be performed using amultilateration algorithm. In this stage, the receiver of the observerperforms geolocation to determine (1) the coordinates of the LoSscatterers (scatterers in the line-of-sight of the receiver antennas),and (2) the times T of emission (reflection) from each of thesescatterers, of the signals from those scatterers are acquired. Thecoordinates of the LoS scatterers may be derived by applyingmultilateration to the TDoA information across the antenna array, andthe timing information can be derived from the actual timing of theechoes and the distances from the LoS scatterers and the antennas.

Viewed from the perspective of these scatterers, however, the signal wasable to reach them, hence they must also see something which appears tobe a LoS source. They may in fact have a direct LoS to the sourcetransmitter; alternatively, if they do not have LoS to the sourcetransmitter, they will have a LoS to a second set of scatterers (whichanalogously will have LoS to the source transmitter or otherscatterers). The coordinates of the first set of scatterers enable themto act as a new virtual “observer” array. Also, the calculated emissiontimes T acquired as the output of the first stage, now become the timesof arrival for the second stage. The multilateration algorithm is thenapplied again in the next stage, geolocating the location and timinginformation (i.e., the coordinates and the times of emission) on thesecond set of scatterers. This process continues with additional stages,as needed, until the coordinates and timing of the transmission sourcesare acquired.

Let T represents the time relative to t=0 when it emitted the originalsignal. Since t=0 may be defined relative to the arrival time of one ofthe signals on the observer array, the T values associated with thescatterers are typically negative numbers. This simply indicates thatthe signals were emitted before they arrived at the antenna array.

Through application of this algorithm, the system of the observer (e.g.,one or more computerized receivers with antennas) not only geolocatesthe source transmitter, but may also provide all or some of thegeolocation information for every scatterer (or selected scatterers) inthe channel through which the signal from the source transmittertraveled to the antenna array of the observer. The system thus possessesthe ability to perform bias-free geolocation even in strictly NLoSchannels, by systematically rebuilding the spatial correlation that wasdestroyed by the NLoS/multipath conditions.

Let us now turn to the Spatial Consistency Algorithm mentioned earlier.In a rich scattering environment, the observable channel impulseresponse (CIR) may be very complex. If we assume that each antennaelement views the same scatterers or sources from slightly differentangles and distances, however, then there may be certain unique patternsthat generally must be followed by the arrival sequences across theantenna array. These can be used to assign different multipath echoes tothe scatterer which reflected them to the antenna.

For illustration purposes, FIGS. 2 and 3 show a scenario in which asource illuminates four scatterers S1-S4 that reflect the energy to athree-element antenna array A1-A3. In this example, there is no directlink/path from the source to the antenna array (NLoS). The first rule ofthe Spatial Consistency Algorithm places a band with a width equal tothe maximum delay between antennas A1-A3 in the array over the multipathsignatures. Signatures from a single scatterer do not spread more thanthe width of this band. The first band is aligned with the earliestarriving multipath echo.

In the illustrated case, the echoes are well separated, so the echoesassociated with scatterer S1 are uniquely identified. Continuing withthe process, the band is aligned with the earliest arriving second echo.Subsequent applications of this rule identify which scatterers areassociated with each multipath echo.

A second example, illustrated in FIGS. 4 and 5, shows a case where thereis some overlap of the multipath echoes (the two right-most bandscorresponding to S3 and S4). This triggers the second layer of theSpatial Consistency Algorithm. Here, the result is still easilyachieved, but more complex cases are possible. In this case, the band isplaced with its left-most or earliest edge on the earliest arrivingscatterer in the region marked S3. It can be seen that there may be someconfusion as to which multipath peak on A2 belongs to the scatterer S3.However, selecting the wrong peak will create a violation of the secondlayer of the consistency algorithm which identifies the multipatharrival sequencing options and by examination of FIG. 5 we can see thatthere is no configuration of scatterers that will allow the signalarriving on A2 to arrive later than both A1 and A3.

Consequently, the only valid option is that the first (left-most) of themultipath spikes that lies in the band labeled S3 on array elementlabeled A2 is the correct option for the reflection from the thirdscatterer. This is a simple application of the Spatial ConsistencyAlgorithm, which excludes potential scatterer configurations thatcorrespond to impossible relative locations of the scatterers and theantennas. The process can be applied in much more complex situations,and it will identify the correct configuration of scattering returnsallowing the multilateration algorithm to be correctly applied.

A more complex application of the process was used to assign the signalsto a variety of scatterers that will be used in the cityscape simulationexample described later in this document.

Next, linearization of the multilateration algorithm (“linearizedmultilateration”) mentioned above is described. Multilaterationessentially means that a distance travelled from a source to a receiveantenna by electromagnetic energy (we will refer to this generically as“light” for simplicity, although it is not assumed that we are referringto visible light) can be correlated with the time taken to travel thatdistance, by multiplying the time by the speed of wave propagation.(Again, although references are made to the speed of “light” in themedium of interest (e.g., air, vacuum) denoted by the letter c forsimplicity in RF applications, another speed may be applicable,particularly in ultrasound and other non-RF applications.) This can bedescribed by the following family of equations:

(X−x _(i))²+(Y−y _(i))²+(Z−z _(i))² =c ²(T+t _(i))²  (1.1)

where X, Y, Z denote the coordinates of the source we are trying togeolocate; (x_(i), y_(i), z_(i)) denote the coordinates of the ithobserver array element, or the ith element in the virtual scatteringarray that we are using; T denotes the emission time of the transmissionsource being geolocated with respect to t=0; and t_(i) denotes the timeof arrival with respect to the agreed t=0 reference used. Hence T willnormally be a negative number, because it denotes that the signal wasemitted before it was received on the array.

In this equation, (X, Y, Z, T) are the unknowns. This is a highlynon-linear equation which may require sophisticated digital signalprocessing (DSP) techniques to solve. In addition, it may not bepossible to find a unique solution to the equations, because every term((X−x_(i)) and similar terms) can in principle have both a positive andnegative value for the solution, the sign being removed by the squaringoperation.

The non-linearity of the problem can be removed or reduced, however, ifit is noted that by taking the differences of these equations betweenpairs of antennas, the equations for the ith antenna can be rewritten as

(X ² +Y ² +Z ² −c ² T ²)−2x _(i) X−2y _(i) Y−2z _(i) Z−2c ² t _(i) T=c ²t _(i) ² −x _(i) ² −y _(i) ² −z _(i) ²,  (1.2)

and for the jth antenna as

(X ² +Y ² +Z ² −c ² T ²)−2x _(i) X−2y _(i) Y−2z _(i) Z−2c ² t _(j) T=c ²t ² −x _(j) ² −y _(j) ² −z _(j) ².  (1.3)

By subtracting these two equations, the squared terms in X, Y, Z, and Tdrop out leaving

(x _(i) −x _(j))X+(y _(i) −y _(j))Y+(z _(i) −z _(j))Z+c ²(t _(i) −t_(j))_(i) T=0.5[(x _(i) ² −x _(j) ²)+(y _(i) ² −y _(j) ²)+(z _(i) ² −z_(i) ²)−c ²(t _(i) ² −t _(j) ²)]   (1.4)

which can be rewritten as

( X _(ij))X+( Y _(ij))Y+( Z _(ij))Z+c ²( T _(ij))=K _(ij) ²,  (1.5)

where X _(ij)=x_(i)−x_(j) and K_(ij) ²=0.5[(x_(i) ²−x_(j) ²)+(y_(i)²−y_(j) ²)+(z_(i) ²−z_(j) ²)−c²(t_(i) ²−t_(j) ²)].

This is a linear equation with four unknowns (X, Y, Z, T). Hence, itrequires four sets of equations for a unique solution. To obtainsolutions to these equations, four antennas may be used. We obtain theij difference terms by selecting four of the available

$N = {\begin{pmatrix}4 \\2\end{pmatrix} = 6}$

differences between the signals and coordinates of antennas (i.e.,(2-1), (3-1), (3-2), (4-1), (4-2), or (4-3)). The solution to thisequation can then be expressed in matrix form, thus:

$\begin{matrix}{\begin{bmatrix}X \\Y \\Z \\{cT}\end{bmatrix} = {{\begin{bmatrix}{\overset{\_}{X}}_{12} & {\overset{\_}{Y}}_{12} & {\overset{\_}{Z}}_{12} & {c{\overset{\_}{T}}_{12}} \\{\overset{\_}{X}}_{13} & {\overset{\_}{Y}}_{13} & {\overset{\_}{Z}}_{13} & {c{\overset{\_}{T}}_{13}} \\{\overset{\_}{X}}_{14} & {\overset{\_}{Y}}_{14} & {\overset{\_}{Z}}_{14} & {c{\overset{\_}{T}}_{14}} \\{\overset{\_}{X}}_{23} & {\overset{\_}{Y}}_{23} & {\overset{\_}{Z}}_{23} & {c{\overset{\_}{T}}_{23}}\end{bmatrix}^{- 1}\begin{bmatrix}K_{12}^{2} \\K_{13}^{2} \\K_{14}^{2} \\K_{23}^{2}\end{bmatrix}}.}} & (1.6)\end{matrix}$

The above equation can be solved by a simple inversion of the matrix:

$\begin{matrix}{A = {\begin{bmatrix}{\overset{\_}{X}}_{12} & {\overset{\_}{Y}}_{12} & {\overset{\_}{Z}}_{12} & {c{\overset{\_}{T}}_{12}} \\{\overset{\_}{X}}_{13} & {\overset{\_}{Y}}_{13} & {\overset{\_}{Z}}_{13} & {c{\overset{\_}{T}}_{13}} \\{\overset{\_}{X}}_{14} & {\overset{\_}{Y}}_{14} & {\overset{\_}{Z}}_{14} & {c{\overset{\_}{T}}_{14}} \\{\overset{\_}{X}}_{23} & {\overset{\_}{Y}}_{23} & {\overset{\_}{Z}}_{23} & {c{\overset{\_}{T}}_{23}}\end{bmatrix}.}} & (1.7)\end{matrix}$

We are attempting to solve for (X, Y, Z, T) rather than the more basic(X, Y, Z). The inclusion of T as an unknown in this equation allows togeolocate in steps where the calculated T values for one set ofscatterers become the Tij values for the subsequent steps.

The linearization process allows solution of the equations by a matrixinversion. The inverse of a 4×4 matrix can be written as follows:

$\begin{matrix}{A^{- 1} = {{\frac{1}{\det (A)}\begin{bmatrix}C_{11} & C_{12} & C_{13} & C_{14} \\C_{21} & C_{22} & C_{23} & C_{24} \\C_{31} & C_{32} & C_{33} & C_{34} \\C_{41} & {C\;}_{42} & C_{43} & C_{44}\end{bmatrix}}.}} & (1.8)\end{matrix}$

The term det(A) in the equation above represents the determinant of thematrix and the terms Cij are the cofactors of the matrix. This techniquefails when det(A)=0. However, from linear algebra it is known thatdet(A) can equal zero only under certain conditions. The determinant ofmatrix is zero if:

1. any one or more rows or columns are zero;

2. any two rows or columns are identical or are multiples of each other;or

3. any row or column can be expressed as a linear sum of any other rowsor columns.

It can be seen that certain geometrical arrangements of the antennascreate precisely this condition. For example, a perfectly linear(inline) array of antennas will violate one or more of the threeconditions noted above. If all the antennas lie in a single plane, asimilar violation occurs. In fact, the determinant non-singularitycondition requires that the following geometrical condition is met:

r ₁₂·(r ₁₃ ×r ₁₄)≠0.  (1.9)

for any combination l, m, n of the vectors in the geometrical arraydiagram (an example of which is shown in FIG. 6), where l, m, n can beany combination of the pairs (12), (13), (14), assuming node 1 is theelement from which the three vectors radiate.

In embodiments, the position vectors of the antenna elements satisfy thearray spatial diversity condition (1.9). In embodiments, the scatterersare chosen so that this condition is satisfied at each stage of themulti-hop (multi-stage) calculation.

The above condition is the most general condition for 3-D geolocation.

For 2-D geolocation, three antennas may be used, and the non-singularitycondition requires only that they are coplanar, but not collinear. Thegeometrical condition satisfying this condition is this:

(r ₁₂ ×r ₁₃)≠0.  (1.10)

The conditions for 3-D and 2-D intrinsically determine in advancewhether a particular antenna array configuration will enable successfulgeolocation.

An example of this geolocation technique is described with reference toFIG. 7. A source and an observer are placed in a strict NLoS 2-Dcityscape environment shown. Any signals emitted by the source onlyreach the observer by reflecting off sets of scatterers. For thissimulation, two sets of scatterers are used. One set has direct LoS tothe observer and a second set has direct LoS to the source. Eachscatterer set has direct LoS to the other scatterer set. In thesimulation, a large number of scatterers were available, but, in orderto maintain simplicity, only the minimum number of scatterers requiredto perform geolocation were actually used for the calculations.

The ToAs of the various multipath impulse responses are plotted versustime for each of three antennas in the diagram of FIG. 8. In thediagram, each dot represents a detected multipath impulse on each of thearray elements. The arrival time can be determined by projecting thepoint down to the x-axis and reading the TDoA value with respect to theearliest arriving pulse.

When the Spatial Consistency Algorithm is applied for a known set ofobserver array coordinates (see FIG. 9), it can be seen that thesignatures are grouped according to various scatterer designations wheresij denote the scatterers that have LoS to the observer. So, forexample, all the points lying within the boundaries that enclose s16represent signals reaching the observer array antennas O1 to O3 atvarious arrival times after reflecting from scatterer s16. Althoughdifficult to see in this diagram, there are five points on each arrayelement between the s16 boundaries. In this case the first point arrivesfrom the scatterer s21 via the scatterer s16. The second point (lyingalmost on top of a third point) represents signal that travelled via thescatterer s22 and s16, etc. If the Geolocation algorithm is then appliedto each set of points in turn, a single set of spatial coordinates fors16 repeated five times but with five different arrival times for eachoccurrence is obtained. This means that s16 was illuminated by fivedifferent additional scatterers.

A concise and simplified summary of the results for this example isshown in FIG. 10. To keep the diagram simple, the results of only threescatterers at each location are used, although more results wereactually calculated.

The results on the right hand side of the diagram show the geolocationof the first set of scatterers. The (X, Y) coordinates of scattererss14, s15 and s16 are shown, each of them indicating five differentarrival times. Three of the arrival times are selected, and in stage 2of the process three additional scatterers, s23, s24, and s25 areidentified, along with a single arrival time for each scatterer. Thesingle arrival time indicates that there is one common sourceilluminating each of these scatterers, and the third geolocationiteration is applied to identify the source location and emission(reflection) time. While performing the simulation, originally threescatterers (s11, s12, and s13) were used with identical x coordinatesand the first pass failed the spatial non-singularity condition; adifferent set of scatterers then needed to be selected. As can be seenfrom the chart, the x coordinates were x=50, 50, and 55 m, whereas thefirst time they were x=50, 50, and 50 m. This means the scatterers werecollinear and unable to uniquely geolocate the source. Thus, inembodiments, the selection of scatterers is performed so that at eachstep the selected scatterers satisfy the non-singularity condition.

In more general cases, four or more antennas may be used to calculatethe differential times of arrival, and then the difference betweenantenna pairs (e.g., antenna pairs 1,2, and 1,3, and 1,4) arecalculated. In the example shown above, differences calculated betweenantenna pairs 1,2 and 1,3 and 2,3 were used. This example was set up towork with this configuration to keep illustrative diagrams simple, butmore generally, the condition where antenna pairs utilize pairs thathave already been utilized may be avoided. For example, if the pairs 1,2and 1,3 are used, then 2,3 may create problems since both 2 and 3 havebeen utilized previously. However, if 1,4 is used, then it can beguaranteed that this pair will provide unique information.

At each stage of this iteration we calculate not only the coordinates ofthe scatterers, but also the time of arrival (which is also the time ofemission/reflection) of the signals from each scatter. It is thecombination of both the spatial coordinates and time results that allowthe use of each set of scatterers as a virtual antenna array to locatethe next set of scatterers. In order to act as a geolocation array, thecoordinates and the ToA of the signals of each element of the arrayshould be determined.

There are many variants of this technique that can be used. For example,it may be possible to use the observer array as an active source toilluminate an otherwise NLoS passive target. In this case the activesource is now one or more of the array elements, but the algorithm canstill be applied, because even though we are now interested in a fullround trip cycle of the signal, the situation is still substantively thesame and we will effectively geolocate the intended target as ascatterer. However, the situation is more complex in that both forwardscattering and backscattering may be encountered, and it may not be atrivial task to identify which of the scatterers that have beengeolocated is the intended target.

Another problem that may arise occurs when the signal-to-noise ratio(SNR) of the signal emitted from an active scatterer is very weak due tomultiple scattering before it reaches the observer. One possibility inthis process is to use the array in an active manner to geolocate thefirst set of scatterers that are LoS to the array. Once scatterers inthe first set of scatterers are accurately identified, it is easier togeolocate any subsequent scatterers. However, a problem with this isthat the active emission by the array may illuminate many scattererswhich are not visible to the signal emitted by the transmission sourcesought to be located. Although there should in theory be some scattererscommon to both processes, it may be difficult to identify them in richscattering environments. Time-reversal precoding can be used to solvethis problem. If the observer array captures the incoming signals fromthe source, time-reverses the captured multipath signatures, andre-emits them back to the source, the time reversal process causes theobserver array to automatically focus the signals only on the scattererswhich were involved in the downward path, and to provide both array gainand multipath gain. This greatly de-emphasizes any scatterers that maygenerate signals in the reverse direction but were not visible in theforward direction, and increases the signals emitted by the intendedscatterers. (Forward direction here means the direction from the sourcesought to be located to the observer antenna array; backward directionis the opposite direction.)

Time reversal techniques are described in International PatentApplication Number PCT/US 12/36180, entitled DISTRIBUTED CO-OPERATINGNODES USING TIME REVERSAL, which is commonly owned with the presentapplication, and in which the inventor of the present application is oneof the named inventors, and which is hereby incorporated by reference inits entirety as if fully set forth herein, including text, figures,claims, tables, computer program listing appendices, matter incorporatedby reference in the patent document, and all other matter in thedocument.

Next, the use of the above techniques is described as they are appliedto GPS enhancement. Global Positioning Satellite systems may not workwell (or work at all) in environments without direct line-of-sightbetween the GPS receiver and the GPS satellites. Examples of typicalenvironments that experience these problems are indoor environments,large cities with tall buildings, woods and other areas under continuoustree canopies, caves, hangers, and other areas with limited visibilityof the sky. An example of a city environment with difficult GPSreception is illustrated in FIG. 11.

This deficiency of GPS systems is not commonly understood, because mostpeople experience GPS systems only in their vehicles, and the vehiclesdo not require continuous GPS coverage. Many vehicle-based GPS systemscan determine their positions relative to an initial GPS location bymonitoring the movement of the vehicle and confining the position to themost likely location on a map. In other words, satellite positiondetermination may be supplemented by one or more other techniques, suchas dead reckoning, inertial navigation, and/or map matching. Infrequentupdating is all that may be needed to maintain reasonable accuracy inthis type of application. But if the vehicle system is unable toinitialize its position or update it within some period of time orwithin some distance of travel, the vehicle GPS system may fail indetermining its correct location.

Failure of a GPS system may be merely annoying in a civilian setting. Itis more serious for the military and law enforcement personnel operatingin cluttered cities and similar environments. Rapid deployment is oftena necessity in such settings, and it may not be possible to obtain aninitial location. It may also be useful for people in the miningindustry and entities responsible for underground rescue to be able toperform accurate geolocation.

The techniques for geolocating a transmission source described in thisdocument can be advantageously employed to improve geolocation,particularly where direct line-of-sight between the receiver (whichattempts to self-geolocate) and one or more GPS satellites is impairedor unavailable. This approach is described below and illustrated in FIG.12.

In embodiments, a beacon or a relay station obtains its own coordinates.The relay station may store the coordinates and/or obtain themdynamically, for example, using at least in part GPS satellites, othertechniques, or combinations of techniques. In particular, the relaystation may be mobile and continuously, continually, periodically, orotherwise measure and update its own coordinates using GPS, possibly incombination with dead reckoning, inertial navigation, map matching,and/or other techniques. It may also receive its own coordinates from alocal or remote human operator or a machine source. In a particularexemplary embodiment, the relay station has full LoS visibility of thesky and is capable of measuring its own position accurately from thesignals of GPS satellites.

The relay station then transmits its signal (or signals) carryinginformation from which the current coordinates of the relay station canbe determined. In other words, the signal(s) transmitted by the relaystation include embedded information from which the current coordinatesof the relay station can be determined; for example, this information ismodulated onto the signal(s). The relay station may send the signal(s)to the observer in a hostile environment. The signal(s) may be in theRF/microwave part of the electromagnetic spectrum, and the observer mayhave a radio receiver compatible with the relay station's signal(s). Thesignals of the relay station may be specifically designed for detectionby the observer's receiver, for example, be transmitted at a power levelthat is higher than the GPS signals, and/or in a different frequencyband.

This arrangement, however, may not solve all problems, because theobserver/receiver (which is trying to self-geolocate and may be deprivedof LoS to one or more needed satellites) may also not have LoS to therelay station. If the channel between the observer/receiver and therelay station is non-line-of-sight, then conventional techniques may notbe helpful in accurately determining the relative positioning of therelay and the observer/receiver. The observer/receiver needs thisinformation (relative position) to accurately calculate its coordinatesby applying a correction and offset to the GPS data sent in thesignal(s) of the relay station.

The techniques for geolocating a non-line-of-sight transmitter may beemployed by the observer/receiver. The techniques allow theobserver/receiver to geolocate the relay station, often with highaccuracy. The relay station may be receiving the GPS signals (orotherwise know its coordinates) even when the observer/receiver isburied in a severe NLoS and high multipath environment. Indeed, the useof multipath may be the only way to detect a signal emitted from asource (e.g., from the relay station) which is NLoS to theobserver/receiver. Hence an algorithm that is capable of decoding thespatial correlation embedded in the multipath signal is quite useful.

In operation, the observer/receiver attempts to read the content of thesignal (or signals, as the case may be) transmitted from the relaystation. The signal contains the coordinates (e.g., GPS coordinates) ofthe relay station. This step of the process may be performed as in thecase of a conventional communication channel. Additionally,time-reversal precoding or other matched filter detection techniques maybe used to enhance the accuracy of this step, particularly when themultipath would render a conventional system unavailing, for example,due to the multipath decay and the consequent intersymbol interference.This step may be performed by using the same antenna or antenna arraythat the observer/receiver uses to perform geolocation, or a differentantenna or antenna array.

Note that the observer may already know the location of the relaystation in advance, by some pre-agreed communication or initializationprocedure, particularly if the relay station is static.

Another step of the geolocation process is the application of any of thetechniques described above (i.e., geolocation in the presence of severemultipath or even in NLoS conditions) for determining the position ofthe relay station relative to the observer/receiver. Theobserver/receiver may first perform a deconvolution of the signalreceived from the relay station to remove the effect of pulse shapingand to recover the true time of arrival of the multipath echoes. Whenthe observer/receiver has acquired this information through its antennas(e.g., three or more antennas or one antenna moved to multiple differentlocations), consistent with the requirements of the techniques, theobserver/receiver applies the techniques described above to geolocateany scatterers in the path between the relay station and theobserver/receiver, and then uses the scatterers as a virtual array togeolocate either a next set of scatterers or the relay station itself.Recall that the observer/receiver has direct LoS to the first set ofscatterers. The observer/receiver can use the first set of scatterers asthe virtual antenna array to geolocate a second set of scatterers, whichhave LoS visibility to the first set of scatterers, and the process cancontinue until the last set of scatterers has direct LoS visibility ofthe relay station. The relay station is then geolocated, resulting inthe observer/receiver obtaining the knowledge of the relative offset(positional difference) between itself and the relay station.

The observer/receiver may then add this relative offset to the absoluteposition of the relay station information. Recall that the absoluteposition of the relay station was obtained in the course of the first ofthe steps described above.

As an additional benefit, this procedure also enables theobserver/receiver to set its time reference system to an accurate time,because the geolocation algorithm also calculates the time offset atwhich the relay station received its GPS coordinates compared to theobserver/receiver clock. Suppose the observer/receiver defines its timebase as having zero offset. Suppose further that the observer/receivercalculates that the relay has a time offset of −10 microseconds relativeto its own time base. Then, to calibrate its clock, theobserver/receiver can simply add 10 microseconds to the accurate GPSephemeris time that was sent by the relay station, because theobserver/receiver “knows” the relay station emitted its signal 10microseconds before the observer/receiver detected the signal.

The procedure described thus allows an observer/receiver to calibrateboth its position and its time reference to a GPS signal in severe NLoSconditions dominated by multipath.

FIG. 13 shows selected components of a system 1300 that can be used forgeolocation and/or GPS enhancement described above. The system includesone or more processors 1305 and one or more memories 1310 storing codeexecutable by the one or more processors 1305 to perform some or all ofthe steps of the methods/procedures. The system further includes one ormore antennas 1315, and one or more receivers 1320 configured to receivesignals (e.g., RF/microwave signals). The one or more receivers 1320 arealso coupled to the one or more processors 1305, which can, undercontrol of the code, configure the one or more receivers 1320 and readinformation from the receivers 1320. The system 1300 may also includeone or more transmitters 1325. The one or more processors 1305 may,under control of the code, configure the transmitters 1325, toilluminate the object sought to be located, and to transmit signalsand/or information to other stations (including, e.g., the relaystation).

One or more buses 1330 may connect the various electronic components(e.g., the processors, memories, receivers, transmitters).

FIG. 14 shows selected steps/bocks of a method 1400 for geolocating anNLoS transmission source from a system of one or more receivers coupledto an antenna array of a plurality of antenna elements.

At flow point 1401, the system is powered up, initialized, and ready toperform the steps of the process.

In step 1405, the system receives and processes signatures ofreflections of a transmission from the source.

In step 1410, the system applies the Spatial Consistency Algorithm todetermine and select a plurality of scatterers that are LoS to thesystem.

In step 1415, the system determines the locations of the scatterers fromthe step 1410, and their respective times of emission/reflection.Multilateration using TDOA analysis may be used for this purpose, as isdescribed above.

In decision block 1418, the system determines whether the scatterersselected and located in the steps 1410 and 1415 satisfy thenon-singularity condition. If the condition is not satisfied, processflow proceeds to step 1420, in which the system records the location ofthe scatterers to exclude at least one of them from selection, and thenreturns to the step 1415 to select a different plurality of scatterersthat are LoS to the system. Note that the new set may include some ofthe scatterers from the previous set(s).

Otherwise, the process flow continues to step 1425, in which the systemuses the last set of scatterers as a virtual antenna array to determine(1) the location(s) and times of emission of the next set of scatterers,or the location of the transmission source; this may be done in themanner identical or analogous to that used in the steps 1410-1420.

In decision block 1430, the system determines whether the transmissionsource has been located. Note that if the locations of the next set ofscatterers are essentially identical, as are the times of emission fromthose scatterers, then this indicates that the next set of scatterers islikely to be the transmission source. If the transmission source has notbeen located, the process flow may go back to the step 1425, and iteratethrough this loop until the transmission source is located.

Otherwise, the process may continue to step 1435, to use the location ofthe source and the time of transmission from the source in one orseveral ways, for example, recording it displaying it, targeting aweapon or a transmission towards it, and/or in another way.

The process may then terminate in flow point 1499, and be repeated asneeded.

As noted above, the system may make this decision based on the locationsothat are or the to determine whether the transmission source has beengeolocated; this can be the direct result of the location of

As those skilled in the art would understand from this document, thedemarcation lines between various blocks and components shown in theFigures are arbitrary to some or even great extent. For example, somecomponents of the receivers may be placed in the processors, and viceversa. Similarly, the memories may be separate from the processors andthe receivers, or included in the receivers and/or processors, and thereceivers and transitters may be combined into transceivers.

Each of the processors 1305 may be a general purpose processor, adigital signal processor (DSP), an application specific integratedcircuit (ASIC), a field programmable gate array (FPGA) or otherprogrammable logic device, or even discrete logic; it can also beimplemented as a combination of such processors and/or logic devices. Ageneral purpose processor may be a microprocessor or a microcontroller.

The geolocating techniques described above can be used advantageously innon-RF applications. For example, blood clots may be located usingdistributed acoustic sensors placed on a person's body, enabling aphysician to perform surgery immediately at a known location. Bloodclots in the body can cause serious strokes or even death. Physiciansusually rely on surgery or drugs to destroy blood clots in the brain,which blood clots might otherwise cause a stroke. Researchers have usedDoppler ultrasound to detect irregularities in blood flow in majorarteries and veins (either blocked or narrowed). Instead, one canperform multilateration of signals using distributed acoustic sensors todetect and geolocate irregularities inside the body. This isparticularly important for high risk patients or during surgery, whenblood clots can be lethal.

Distributed acoustic sensors can also detect and geolocate blood clotsin the brain with distributed sensors placed around a person's skull.The techniques described above can enable pinpoint geolocation of theblood clot in the brain and enable pinpoint targeting by focusedultrasound, to break up the clots. Geolocation of blood clots combinedwith Time Reversal can focus energy onto detected blood clots to breakthem up, with acoustic energy focused at the target irregularity andsparing the surrounding tissue. Body network can be used with an activenon-invasive acoustic source, or using the beating heart as the internalsound source, with passive listening.

Although steps and/or decision blocks of various methods may have beendescribed serially in this disclosure, some of these steps and decisionsmay be performed by separate elements in conjunction or in parallel,asynchronously or synchronously, in a pipelined manner, or otherwise.There is no particular requirement that the steps and decisions beperformed in the same order in which this description lists them and theaccompanying Figures show them, except where explicitly so indicated,otherwise made clear from the context, or inherently required. It shouldbe noted, however, that in selected examples the steps and decisions areperformed in the particular progressions described in this documentand/or shown in the accompanying Figures. Furthermore, not everyillustrated step and decision may be required in every embodiment, whilesome steps and decisions that have not been specifically illustrated maybe desirable or necessary in some embodiments.

As is known to those skilled in the art, data, instructions, signals,and symbols may be carried by voltages, currents, electromagnetic waves,acoustic waves, other analogous means, and their combinations.

As is also known to those skilled in the art, blocks, modules, circuits,and steps described in this documents may be embodied as electronichardware, software, firmware, or combinations of hardware, software, andfirmware. Whether specific functionality is implemented as hardware,software, firmware or a combination, this description is intended tocover the functionality. Some illustrative blocks, modules, circuits,and analogous elements described in this document may be implementedwith a general purpose processor, a special purpose processor (such asan application specific integrated circuit-based processor), aprogrammable/configurable logic device, discrete logic, other discreteelectronic hardware components, or combinations of such elements. Ageneral purpose processor may be, for example, a microcontroller or amicroprocessor. A processor may also be implemented as a combination ofcomputing devices, for example, a plurality of microprocessors, one ormore microprocessors in conjunction with one or more microcontrollersand/or one or more digital signal processors, or other analogouscombination.

The instructions (machine executable code) corresponding to the methodsteps of this disclosure may be embodied directly in hardware, insoftware, in firmware, or in combinations thereof. A software module maybe stored in volatile memory, flash memory, Read Only Memory (ROM),Electrically Programmable ROM (EPROM), Electrically ErasableProgrammable ROM (EEPROM), hard disk, a CD-ROM, a DVD-ROM, or other formof non-transitory storage medium known in the art. An exemplary storagemedium is coupled to the processor such that the processor can readinformation from, and write information to, the storage medium. In analternative, the storage medium may be integral to the processor. Theinstructions can also be transmitted over a transmission medium, forexample, over electrical wiring or cabling, through optical fiber,wirelessly, or by any other form of physical transmission. Thetransmission can take place over a dedicated link betweentelecommunication devices, or through a wide- or local-area network,such as the Internet, an intranet, extranet, or any other kind of publicor private network.

In this description, the focus was on one or more exemplary scenarios,but the techniques may be applicable to almost any variant of theexemplary scenarios and other scenarios.

The system and process features described throughout this document maybe present individually, or in any combination or permutation, exceptwhere presence or absence of specificfeature(s)/element(s)/limitation(s) is inherently required, explicitlyindicated, or otherwise made clear from the context.

This document describes in detail the inventive apparatus, methods, andarticles of manufacture for image capture and processing. This was donefor illustration purposes only and, therefore, the foregoing descriptionis not necessarily intended to limit the spirit and scope of theinvention(s) described. Neither the specific embodiments of theinvention(s) as a whole, nor those of its or their features necessarilylimit the general principles underlying the invention(s). The specificfeatures described herein may be used in some embodiments, but not inothers, without departure from the spirit and scope of the invention(s)as set forth herein. Various physical arrangements of components andvarious step sequences also fall within the intended scope of theinvention(s). Many additional modifications are intended in theforegoing disclosure, and it will be appreciated by those of ordinaryskill in the pertinent art that in some instances some features will beemployed in the absence of a corresponding use of other features. Theembodiments described above are illustrative and not necessarilylimiting, although they or their selected features may be limiting forsome claims. The illustrative examples therefore do not necessarilydefine the metes and bounds of the invention(s) and the legal protectionafforded the invention(s).

What is claimed is:
 1. A process of geolocation of at least one radiofrequency (RF) transmission source using a antenna array, the processcomprising steps of: locating a first plurality of scatterers withinline-of-sight (LoS) of the antenna array, wherein for each scatterer ofthe first plurality of scatterers coordinates and time of emission areestimated; locating the at least one RF transmission source based on thecoordinates and the times of emission estimated for the first pluralityof scatterers, thereby obtaining coordinates of the at least one RFtransmission source; and providing the coordinates of the at least oneRF transmission source, the step of providing comprising at least one ofdisplaying, storing, and transmitting coordinates of the at least one RFtransmission source.
 2. A process of geolocation according to claim 1,wherein the step for locating the first plurality of scatters isperformed using (1) Spatial Consistency algorithm, and (2)multilateration based on time difference of arrival (TDoA) of signals atthe antenna array.
 3. A process of geolocation according to claim 2,wherein the antenna array is located non-line-of-sight (NLoS) to the atleast one RF transmission source, and wherein geolocation bias errorsare reduced or eliminated.
 4. A process of geolocation according toclaim 3, wherein at least one scatterer of the first plurality ofscatterers is located non-line-of-sight to the at least one RFtransmission source.
 5. A process of geolocation according to claim 3,wherein at least two scatterers of the first plurality of scatterers arelocated non-line-of-sight to the at least one RF transmission source. 6.A process of geolocation according to claim 3, wherein each scatterer ofthe first plurality of scatterers is located non-line-of-sight to the atleast one RF transmission source.
 7. A process of geolocation accordingto claim 3, wherein the step of locating the at least one RFtransmission source comprises iteratively determining coordinates andtimes of emission at a next set of scatterers within LoS of a previousset of scatterers until coordinates of the at least one RF transmissionsource are determined, wherein the step of iteratively determiningcomprises applying the Spatial Consistency algorithm and multiaterationbased on TDoA at each iteration, and wherein the multilateration islinearized.
 8. A process of geolocation according to claim 7, whereinthe step of locating the at least one RF transmission source comprisesensuring satisfaction of a non-singularity condition at said eachiteration.
 9. A process of geolocation according to claim 3, wherein theat least one transmission source consists of a single RF transmissionsource.
 10. A process of geolocation according to claim 3, wherein theat least one transmission source comprises a plurality of RFtransmission sources, and wherein coordinates of at least two RFtransmission sources of the plurality of RF transmission sources areidentified.
 11. A process of geolocation of one or more transmissionsources in a non-line-of-sight (NLoS) path from at least one receiverwith a plurality of antenna elements, comprising: geolocating scatterersthat are line-of-sight (LoS) to the plurality of antenna elements; afterthe step of geolocating the scatterers that are LoS to the plurality ofantenna elements, using previously located scatterers as a virtual arrayto geolocate a next set of scatterers or the one or more transmissionsources, the step of using the previously located scatterers beingrepeated until coordinates of the one or more transmission sources areobtained; and at least one of displaying, storing, and transmitting thecoordinates.
 12. A process of geolocation according to claim 11, whereinthe step of geolocating the scatterers that are LoS comprises applyingSpatial Consistency algorithm, performing multilateration based on timedifference of arrival (TDoA) of signals, and selecting scatterers thatsatisfy a non-singularity condition.
 13. A geolocation systemcomprising: an antenna array comprising a plurality of antenna elements;at least one receiver coupled to the antenna array and configured toreceive signals from each antenna element of the array; and at least oneprocessor coupled to the at least one receiver to obtain informationderived from the signals; wherein the processor is configured to locatea first plurality of scatterers within line-of-sight (LoS) of theantenna array by estimating coordinates and time of emission for eachscatterer of a first plurality of scatterers that scatter a signaltransmitted by at least one non-line-of-sight (NLoS) radio frequency(RF) transmission source; locate the at least one RF transmission sourcebased on the coordinates and the times of emission estimated for thefirst plurality of scatterers, thereby obtaining coordinates of the atleast one RF transmission source; and provide the coordinates of the atleast one RF transmission source by at least one of displaying, storing,and transmitting the coordinates of the at least one RF transmissionsource.
 14. A system according to claim 13, wherein the at least oneprocessor is further configured to locate the first plurality ofscatters using (1) Spatial Consistency algorithm, and (2) linearizedmultilateration based on time difference of arrival (TDoA) of signals atthe antenna array.
 15. A system according to claim 14, wherein the atleast one processor is configured to determine iteratively coordinatesand times of emission at a next set of scatterers within LoS of aprevious set of scatterers until the at least one RF transmission sourceis identified, by applying the Spatial Consistency algorithm andmultilateration based on TDoA at each iteration, and wherein themultilateration is linearized.
 16. A system according to claim 15,wherein the at least one processor is further configured to ensuresatisfaction of a non-singularity condition at each iteration.
 17. Anarticle of manufacture comprising machine-readable storage medium withprogram code stored in the medium in a non-volatile manner, the programcode, when executed by at least one processor of a system comprising anantenna array with a plurality of antenna elements, at least onereceiver coupled to the antenna array, and at least one processorcoupled to the at least one receiver, configures the system to: locate afirst plurality of scatterers within line-of-sight (LoS) of the antennaarray, wherein for each scatterer of the first plurality of scattererscoordinates and time of emission are estimated; locate the at least oneRF transmission source based on the coordinates and the times ofemission estimated for the first plurality of scatterers, therebyobtaining coordinates of the at least one RF transmission source; andprovide the coordinates of the at least one RF transmission source by atleast one of displaying, storing, and transmitting the coordinates ofthe at least one RF transmission source.